Home About us Contact
|
Home About us Contact | ||
|
|
||
Improved Prediction (improved + prediction)
Selected AbstractsImproved Prediction of Nonepileptic Seizures with Combined MMPI and EEG MeasuresEPILEPSIA, Issue 3 2000D. Storzbach Summary: Purpose: Nonepileptic seizures (NESs) are frequently mistaken for epileptic seizures (ESs). Improved detection of patients with NESs could lead to more appropriate treatment and medical cost savings. Previous studies have shown the MMPI/MMPI-2 to be a useful predictor of NES. We hypothesized that combining the MMPI-2 with a physiologic predictor of epilepsy (routine EEG; rEEG) would result in enhanced prediction of NES. Methods: Consecutive patients undergoing CCTV-EEG monitoring underwent rEEG evaluation and completed an MMPI-2. Patients were subsequently classified as having epilepsy (n = 91) or NESs (n = 76) by using standardized criteria. Logistic regression was used to predict seizure type classification. Results: Overall classification accuracy was 74% for rEEG, 71% for MMPI-2 Hs scale, and 77% for MMPI-2 Hy scale. The model that best predicted diagnosis included rEEG, MMPI-2, and number of years since the first spell, resulting in an overall classification accuracy of 86%. Conclusions: The high accuracy achieved by the model suggests that it may be useful for screening candidates for diagnostic telemetry. [source] Modelling Spikes in Electricity Prices,THE ECONOMIC RECORD, Issue 263 2007RALF BECKER During periods of market stress, electricity prices can rise dramatically. Electricity retailers cannot pass these extreme prices on to customers because of retail price regulation. Improved prediction of these price spikes therefore is important for risk management. This paper builds a time-varying-probability Markov-switching model of Queensland electricity prices, aimed particularly at forecasting price spikes. Variables capturing demand and weather patterns are used to drive the transition probabilities. Unlike traditional Markov-switching models that assume normality of the prices in each state, the model presented here uses a generalised beta distribution to allow for the skewness in the distribution of electricity prices during high-price episodes. [source] Improved prediction of recurrence after curative resection of colon carcinoma using tree-based risk stratificationCANCER, Issue 5 2004Martin Radespiel-Tröger M.D. Abstract BACKGROUND Patients who are at high risk of recurrence after undergoing curative (R0) resection for colon carcinoma may benefit most from adjuvant treatment and from intensive follow-up for early detection and treatment of recurrence. However, in light of new clinical evidence, there is a need for continuous improvement in the calculation of the risk of recurrence. METHODS Six hundred forty-one patients with R0-resected colon carcinoma who underwent surgery between January 1, 1984 and December 31, 1996 were recruited from the Erlangen Registry of Colorectal Carcinoma. The study end point was time until first locoregional or distant recurrence. The factors analyzed were: age, gender, site in colon, International Union Against Cancer (UICC) pathologic tumor classification (pT), UICC pathologic lymph node classification, histologic tumor type, malignancy grade, lymphatic invasion, venous invasion, number of examined lymph nodes, number of lymph node metastases, emergency presentation, intraoperative tumor cell spillage, surgeon, and time period. The resulting prognostic tree was evaluated by means of an independent sample using a measure of predictive accuracy based on the Brier score for censored data. Predictive accuracy was compared with several proposed stage groupings. RESULTS The prognostic tree contained the following variables: pT, the number of lymph node metastases, venous invasion, and emergency presentation. Predictive accuracy based on the validation sample was 0.230 (95% confidence interval [95% CI], 0.227,0.233) for the prognostic tree and 0.212 (95% CI, 0.209,0.215) for the UICC TNM sixth edition stage grouping. CONCLUSIONS The prognostic tree showed superior predictive accuracy when it was validated using an independent sample. It is interpreted easily and may be applied under clinical circumstances. Provided that their classification system can be validated successfully in other centers, the authors propose using the prognostic tree as a starting point for studies of adjuvant treatment and follow-up strategies. Cancer 2004;100:958,67. © 2004 American Cancer Society. [source] The role of mineral and organic components in phenanthrene and dibenzofuran sorption by soilEUROPEAN JOURNAL OF SOIL SCIENCE, Issue 3 2006R. Celis Summary Improved predictions of sorption of hydrophobic organic compounds (HOCs) in soil require a better knowledge of the relative contribution of inorganic and organic soil constituents to the sorption process. In this paper, sorption of a three-ring polycyclic aromatic hydrocarbon (phenanthrene) and a three-ring heterocyclic,aromatic compound (dibenzofuran) by six agricultural soils, their clay-size fractions, and a series of single, binary, and ternary model sorbents was evaluated to elucidate the relative role of soil mineral and organic components in the retention of these two model HOCs. The sorption coefficients for phenanthrene and dibenzofuran on purified soil organic materials (Kd = 821,9080 litre kg,1) were two orders of magnitude greater than those measured on mineral model sorbents (Kd = 0,114 litre kg,1). This, along with the strong correlation between sorption and the organic C content of the soil clay fractions (r = 0.99, P < 0.01), indicated a primary role of soil organic matter in the retention of both compounds. However, weak relationships between phenanthrene and dibenzofuran sorption coefficients and the organic C content of the bulk soils and variability of Koc values among soils, clay fractions, and model sorbents (1340,21020 litre kg,1 C for phenanthrene and 1685,7620 litre kg,1 C for dibenzofuran) showed that sorption was not predictable exclusively from the organic C content of the materials. Organic matter heterogeneity and domain blockage arising from organic matter,clay interactions and associated pH shifts were identified as the most likely causes of the different organic C-normalized sorption capacities of the soils. A direct contribution from minerals to the sorption of phenanthrene and dibenzofuran by the soils studied was likely to be small. Our results suggested that suitable descriptors for the extent of organic matter,mineral interactions would help to improve current Koc -based sorption predictions and subsequently the assessment of risk associated with the presence of HOCs in soil. [source] Experimental measurements and kinetic modeling of CO/H2/O2/NOx conversion at high pressure,INTERNATIONAL JOURNAL OF CHEMICAL KINETICS, Issue 8 2008Christian Lund Rasmussen This paper presents results from lean CO/H2/O2/NOx oxidation experiments conducted at 20,100 bar and 600,900 K. The experiments were carried out in a new high-pressure laminar flow reactor designed to conduct well-defined experimental investigations of homogeneous gas phase chemistry at pressures and temperatures up to 100 bar and 925 K. The results have been interpreted in terms of an updated detailed chemical kinetic model, designed to operate also at high pressures. The model, describing H2/O2, CO/CO2, and NOx chemistry, is developed from a critical review of data for individual elementary reactions, with supplementary rate constants determined from ab initio CBS-QB3 calculations. New or updated rate constants are proposed for important reactions, including OH + HO2 , H2O + O2, CO + OH , [HOCO] , CO2 + H, HOCO + OH , CO + H2O2, NO2 + H2 , HNO2 + H, NO2 + HO2 , HONO/HNO2 + O2, and HNO2(+M) , HONO(+M). Further validation of the model performance is obtained through comparisons with flow reactor experiments from the literature on the chemical systems H2/O2, H2/O2/NO2, and CO/H2O/O2 at 780,1100 K and 1,10 bar. Moreover, introduction of the reaction CO + H2O2 , HOCO + OH into the model yields an improved prediction, but no final resolution, to the recently debated syngas ignition delay problem compared to previous kinetic models. © 2008 Wiley Periodicals, Inc. Int J Chem Kinet 40: 454,480, 2008 [source] Improving the K6 short scale to predict serious emotional disturbance in adolescents in the USAINTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH, Issue S1 2010Jennifer Greif Green Abstract Effective screening for emotional and behavioral disorders among youth requires brief screening scales with good validity to identify youth requiring further evaluation and to estimate prevalence of target disorders in populations of interest such as schools or neighborhoods. This paper examines the psychometric properties of a very short (six-item) screening scale, the K6, to assess serious emotional disturbance (SED) among youth. The K6, which is made up of symptoms of depression and anxiety, has been shown in previous research to be a strong predictor of serious mental illness (SMI) in adults, but no information is available on the ability of the scale to screen for SED among youth. The current report examines the K6 as a screen for SED in a national survey of US adolescents, the National Comorbidity Survey Replication Adolescent Supplement (NCS-A). The K6 is shown to provide fairly good prediction of SED [area under curve (AUC) = 0.74] that is somewhat higher for internalizing (AUC = 0.80) than behavior (AUC = 0.75) disorders. Based on this result, we augmented the K6 with questions about symptoms of behavior disorders. This improved prediction of SED (from AUC = 0.74 to AUC = 0.83) as well as of SED associated with pure behavior disorders (from AUC = 0.53 to AUC = 0.78). These results show that although the symptoms of depression and anxiety in the K6 are sufficient to detect SMI among adults, high rates of behavior disorders among adolescents require indicators of behavior disorders to be added to the K6 to screen adequately for adolescent SED. Copyright © 2010 John Wiley & Sons, Ltd. [source] Popliteal lymph node assay: facts and perspectivesJOURNAL OF APPLIED TOXICOLOGY, Issue 6 2005Guillaume Ravel Abstract The popliteal lymph node assay (PLNA) derives from the hypothesis that some supposedly immunemediated adverse effects induced by certain pharmaceuticals involve a mechanism resembling a graft-versus-host reaction. The injection of many but not all of these compounds into the footpad of mice or rats produces an increase in the weight and/or cellularity of the popliteal lymph node in the treated limb (direct PLNA). Some of the compounds known to cause these adverse effects in humans, however, failed to induce a positive PLNA response, leading to refinements of the technique to include pretreatment with enzyme inducers, depletion of CD4+ T cells or additional endpoints such as histological examination, lymphocyte subset analysis and cytokine fingerprinting. Alternative approaches have been used to improve further the predictability of the assay. In the secondary PLNA, the test compound is injected twice in order to illicit a greater secondary response, thus suggesting a memory-specific T cell response. In the adoptive PLNA, popliteal lymph node cells from treated mice are injected into the footpad of naive mice; a marked response to a subsequent footpad challenge demonstrates the involvement of T cells. Finally, the reporter antigens TNP-Ficoll and TNP-ovalbumin are used to differentiate compounds that induce responses involving neo-antigen help or co-stimulatory signals (modified PLNA). The PLNA is increasingly considered as a tool for detection of the potential to induce both sensitization and autoimmune reactions. A major current limitation is validation. A small inter-laboratory validation study of the direct PLNA found consistent results. No such study has been performed using an alternative protocol. Other issues include selection of the optimal protocol for an improved prediction of sensitization vs autoimmunity, and the elimination of false-positive responses due to primary irritation. Finally, a better understanding of underlying mechanisms is essential to determine the most relevant endpoints. The confusion resulting from use of the PLNA to predict autoimmune-like reactions as well as sensitization should be clarified. Interestingly, most drugs that were positive in the direct PLNA are also known to cause drug hypersensitivity syndrome in treated patients. This observation is expected to open new avenues of research. Copyright © 2005 John Wiley & Sons, Ltd. [source] Third-Person Effects and the Environment: Social Distance, Social Desirability, and Presumed BehaviorJOURNAL OF COMMUNICATION, Issue 2 2005Jakob D. Jensen Previous research has documented third-person effects (persons presuming that others will be more susceptible to media effects than they themselves are) and explored moderators such as social desirability (the effect reverses when the media effects are undesirable) and social distance (the effect increases as the social distance from the self increases). In a study of environmental news coverage, the authors observed the general third-person effect and the moderating role of social desirability; however, they also found that social distance affected presumed influence in complex ways reflecting varying perceptions of issue relevance for the comparison groups. A new variable, presumed behavior (the presumed effect of media coverage on others' behavior), was found to be independent of presumed influence and to offer improved prediction of perceivers' behavioral intentions. [source] Information About Multiple Risks: The Case of Building and Content InsuranceJOURNAL OF RISK AND INSURANCE, Issue 4 2002Dario Bonato Insurers traditionally use risk-specific characteristics of insureds to classify them according to risk. In this article, the practical relevance of information about multiple risks is demonstrated for the case of content insurance of a Swiss company. Two types of such information prove important: information about "spillover moral hazard" caused by mandated prevention affecting preventive effort in an unregulated line, and information about "common impulses" reflected in the loss experience of related lines. Both contribute to an improved prediction of loss probability. [source] QSAR Study of 2,3-Benzodiazepin-4(thi)one- and 1,2-Phthalazine-Related Negative Allosteric Modulators of the AMPA Receptor: A Structural Descriptors-Based ReassessmentMOLECULAR INFORMATICS, Issue 3 2005Peter Buchwald Abstract In an attempt to establish statistically more rigorous and chemically more meaningful quantitative structure-activity relationship (QSAR) equations, a reassessment of a recent study of in vivo anticonvulsant activity for a set of 2,3-benzodiazepin-4(thi)one- and 1,2-phthalazine-related allosteric AMPA antagonists (n=61) is presented. Contrary to the original, relatively nonspecific descriptor set, which included, for example, a number of topological descriptors, specific structural descriptors that are much easier to interpret from a medicinal chemical point of view are used in this multiple linear regression-based approach. Only statistically significant descriptors have been retained in the final equation, and whereas they give about the same correlation as those of the original paper on the training set (r2 of 0.79 vs. 0.76, n=49), they perform much better on the test set (predictive r of 0.73 vs. 0.05; r2 of 0.78 vs. 0.08, n=12). Descriptors found to be relevant are clearly related to substitutions at known pharmacophore positions, such as those corresponding to the 2,3-, 7,8- and 4,-positions of the benzodiazepine skeleton. Therefore, by a more careful selection of the descriptor set, both an improved prediction and a more intuitive quantitative interpretation could be achieved for this set of allosteric AMPA antagonists. [source] Using an intensity-scale technique to assess the added benefit of high-resolution model precipitation forecastsATMOSPHERIC SCIENCE LETTERS, Issue 2 2006Marion P. Mittermaier Abstract Deterministic precipitation forecasts from the 12- and 4-km versions of the Unified Model (UM) were compared using an intensity-scale technique. Averaging raw model output is always recommended to minimise grid-scale errors. The retained detail in averaged 4-km forecasts produces an improved prediction of larger accumulations. © Crown Copyright 2006. Reproduced with the permission of the Controller of HMSO. Published by John Wiley & Sons, Ltd. [source] Fast FSR Variable Selection with Applications to Clinical TrialsBIOMETRICS, Issue 3 2009Dennis D. Boos Summary A new version of the false selection rate variable selection method of Wu, Boos, and Stefanski (2007,,Journal of the American Statistical Association,102, 235,243) is developed that requires no simulation. This version allows the tuning parameter in forward selection to be estimated simply by hand calculation from a summary table of output even for situations where the number of explanatory variables is larger than the sample size. Because of the computational simplicity, the method can be used in permutation tests and inside bagging loops for improved prediction. Illustration is provided in clinical trials for linear regression, logistic regression, and Cox proportional hazards regression. [source] Ultra scale-down prediction using microwell technology of the industrial scale clarification characteristics by centrifugation of mammalian cell brothsBIOTECHNOLOGY & BIOENGINEERING, Issue 2 2009A.S. Tait Abstract This article describes how a combination of an ultra scale-down (USD) shear device feeding a microwell centrifugation plate may be used to provide a prediction of how mammalian cell broth will clarify at scale. In particular a method is described that is inherently adaptable to a robotic platform and may be used to predict how the flow rate and capacity (equivalent settling area) of a centrifuge and the choice of feed zone configuration may affect the solids carry over in the supernatant. This is an important consideration as the extent of solids carry over will determine the required size and lifetime of a subsequent filtration stage or the passage of fine particulates and colloidal material affecting the performance and lifetime of chromatography stages. The extent of solids removal observed in individual wells of a microwell plate during centrifugation is shown to correlate with the vertical and horizontal location of the well on the plate. Geometric adjustments to the evaluation of the equivalent settling area of individual wells (,M) results in an improved prediction of solids removal as a function of centrifuge capacity. The USD centrifuge settling characteristics need to be as for a range of equivalent flow rates as may be experienced at an industrial scale for a machine of different shear characteristics in the entry feed zone. This was shown to be achievable with two microwell-plate based measurements and the use of varying fill volumes in the microwells to allow the rapid study of a fivefold range of equivalent flow rates (i.e., at full scale for a particular industrial centrifuge) and the effect of a range of feed configurations. The microwell based USD method was used to examine the recovery of CHO-S cells, prepared in a 5,L reactor, at different points of growth and for different levels of exposure to shear post reactor. The combination of particle size distribution measurements of the cells before and after shear and the effect of shear on the solids remaining after centrifugation rate provide insight into the state of the cells throughout the fermentation and the ease with which they and accumulated debris may be removed by continuous centrifugation. Hence bioprocess data are more readily available to help better integrate cell culture and cell removal stages and resolve key bioprocess design issues such as choice of time of harvesting and the impact on product yield and contaminant carry over. Operation at microwell scale allows data acquisition and bioprocess understanding over a wide range of operating conditions that might not normally be achieved during bioprocess development. Biotechnol. Bioeng. 2009; 104: 321,331 © 2009 Wiley Periodicals, Inc. [source] Use of mid-infrared spectroscopy in the diffuse-reflectance mode for the prediction of the composition of organic matter in soil and litterJOURNAL OF PLANT NUTRITION AND SOIL SCIENCE, Issue 3 2008Bernard Ludwig Abstract Mid-infrared spectroscopy (MIRS) is assumed to be superior to near-infrared spectroscopy (NIRS) for the prediction of soil constituents, but its usefulness is still not sufficiently explored. The objective of this study was to evaluate the ability of MIRS to predict the chemical and biological properties of organic matter in soils and litter. Reflectance spectra of the mid-infrared region including part of the near-infrared region (7000,400,cm,1) were recorded for 56 soil and litter samples from agricultural and forest sites. Spectra were used to predict general and biological characteristics of the samples as well as the C composition which was measured by 13C CPMAS-NMR spectroscopy. A partial least-square method and cross-validation were used to develop equations for the different constituents over selected spectra ranges after several mathematical treatments of the spectra. Mid-infrared spectroscopy predicted well the C : N ratio: the modeling efficiency EF was 0.95, the regression coefficient (a) of a linear regression (measured against predicted values) was 1.0, and the correlation coefficient (r) was 0.98. Satisfactorily (EF , 0.70, 0.8 , a , 1.2, r , 0.80) assessed were the contents of C, N, and lignin, the production of dissolved organic carbon, and the contents of carbonyl C, aromatic C, O-alkyl C, and alkyl C. However, the N mineralization rate, the microbial biomass and the alkyl,to,aromatic C ratio were predicted less satisfactorily (EF < 0.70). Limiting the sample set to mineral soils did generally not result in improved predictions. The good and satisfactory predictions reported above indicate a marked usefulness of MIRS in the assessment of chemical characteristics of soils and litter, but the accuracies of the MIRS predictions in the diffuse-reflectance mode were generally not superior to those of NIRS. [source] A method for improving predictions of bed-load discharges to reservoirsLAKES & RESERVOIRS: RESEARCH AND MANAGEMENT, Issue 2 2007Vicente L. Lopes Abstract Effective management options for mitigating the loss of reservoir water storage capacity to sedimentation depend on improved predictions of bed-load discharges into the reservoirs. Most predictions of bed-load discharges, however, are based on the assumption that the rates of bed-load sediment availability equal the transport capacity of the flow, ignoring the spatio-temporal variability of the sediment supply. This paper develops a semiquantitative method to characterize bed-load sediment transport in alluvial channels, assuming a channel reach is non-supply limited when the bed-load discharge of a given sediment particle-size class is functionally related to the energy that is available to transport that fraction of the total bed-load. The method was applied to 22 alluvial stream channels in the USA to determine whether a channel reach had a supply-limited or non-supply-limited bed-load transport regime. The non-supply-limited transport regime was further subdivided into two groups on the basis of statistical tests. The results indicated the pattern of bed-load sediment transport in alluvial channels depends on the complete spectrum of sediment particle sizes available for transport rather than individual particle-size fractions represented by one characteristic particle size. The application of the method developed in this paper should assist reservoir managers in selecting bed-load sediment transport equations to improve predictions of bed-load discharge in alluvial streams, thereby significantly increasing the efficiency of management options for maintaining the storage capacity of waterbodies. [source] Neuro-fuzzy structural classification of proteins for improved protein secondary structure predictionPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 8 2003Joachim A. Hering Abstract Fourier transform infrared (FTIR) spectroscopy is a very flexible technique for characterization of protein secondary structure. Measurements can be carried out rapidly in a number of different environments based on only small quantities of proteins. For this technique to become more widely used for protein secondary structure characterization, however, further developments in methods to accurately quantify protein secondary structure are necessary. Here we propose a structural classification of proteins (SCOP) class specialized neural networks architecture combining an adaptive neuro-fuzzy inference system (ANFIS) with SCOP class specialized backpropagation neural networks for improved protein secondary structure prediction. Our study shows that proteins can be accurately classified into two main classes "all alpha proteins" and "all beta proteins" merely based on the amide I band maximum position of their FTIR spectra. ANFIS is employed to perform the classification task to demonstrate the potential of this architecture with moderately complex problems. Based on studies using a reference set of 17 proteins and an evaluation set of 4 proteins, improved predictions were achieved compared to a conventional neural network approach, where structure specialized neural networks are trained based on protein spectra of both "all alpha" and "all beta" proteins. The standard errors of prediction (SEPs) in % structure were improved by 4.05% for helix structure, by 5.91% for sheet structure, by 2.68% for turn structure, and by 2.15% for bend structure. For other structure, an increase of SEP by 2.43% was observed. Those results were confirmed by a "leave-one-out" run with the combined set of 21 FTIR spectra of proteins. [source] Differential impacts of habitat heterogeneity on male and female connectivity in a spatially structured pest systemAUSTRAL ECOLOGY, Issue 1 2009G. S. HAMILTON Abstract In a previous study, a model of landscape heterogeneity was developed and applied to a spatially structured wild rabbit (Oryctolagus cuniculus) population. That study showed clearly the influence of resource heterogeneity on connectivity levels. The simulation study was based on female movements and used population genetic validation data appropriate for a female study. Most models assume that males and females will exhibit similar patterns, although this has rarely been tested. In the current study we extend the analysis to consider differences between female and male connectivity in the same spatially structured pest system. Amplified fragment length polymorphism (AFLP) markers were screened on the same samples used previously for mtDNA analysis. The mtDNA data were used to validate female results, and AFLP data were used to validate combined male and female results. Connectivity patterns from the two simulations (female, and combined male and female) connectivity patterns showed no association. However, each was concordant with appropriate validation data, showing highly significant associations between pairwise population connectivity and the genetic data. A relative connectivity metric for the combined simulation was regressed against the mean of pairwise ,ST values, with almost 70% of the variation explained by a linear model. Demonstrating differential effects of habitat heterogeneity on male and female connectivity provides further evidence that spatial resource heterogeneity impacts on connectivity. Understanding differences in population connectivity will allow improved predictions of disease spread, local extinctions and recolonizations. Furthermore, modelling such differences in pest systems will allow management plans to be better targeted, for example by strategically introducing diseases for control purposes into populations which exhibit high male connectivity to aid spread, but low female connectivity to inhibit recolonization potential after control. [source] In situ near infrared spectroscopy for analyte-specific monitoring of glucose and ammonium in streptomyces coelicolor fermentationsBIOTECHNOLOGY PROGRESS, Issue 1 2010Nanna Petersen Abstract There are many challenges associated with in situ collection of near infrared (NIR) spectra in a fermentation broth, particularly for highly aerated and agitated fermentations with filamentous organisms. In this study, antibiotic fermentation by the filamentous bacterium Streptomyces coelicolor was used as a model process. Partial least squares (PLS) regression models were calibrated for glucose and ammonium based on NIR spectra collected in situ. To ensure that the models were calibrated based on analyte-specific information, semisynthetic samples were used for model calibration in addition to data from standard batches. Thereby, part of the inherent correlation between the analytes could be eliminated. The set of semisynthetic samples were generated from fermentation broth from five separate fermentations to which different amounts of glucose, ammonium, and biomass were added. This method has previously been used off line but never before in situ. The use of semisynthetic samples along with validation on an independent batch provided a critical and realistic evaluation of analyte-specific models based on in situ NIR spectroscopy. The prediction of glucose was highly satisfactory resulting in a RMSEP of 1.1 g/L. The prediction of ammonium based on NIR spectra collected in situ was not satisfactory. A comparison with models calibrated based on NIR spectra collected off line suggested that this is caused by signal attenuation in the optical fibers in the region above 2,000 nm; a region which contains important absorption bands for ammonium. For improved predictions of ammonium in situ, it is suggested to focus efforts on enhancing the signal in that particular region. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010 [source] | ||||||||||||||||||||||